Method and apparatus for assessing characteristics of liquids

ABSTRACT

A method to perform security screening at an airport on hand-carried baggage. The method includes requesting passengers with hand carried baggage to remove from the baggage a container that holds a liquid and perform an x-ray inspection on the hand carried baggage and on the container while the container remains outside the baggage. According to the method, the results of the x-ray inspection are used to determine if the baggage contains illegal objects and if the liquid is a security threat.

FIELD OF THE INVENTION

The present invention relates to technologies for assessing propertiesof liquids, in particular determining if a liquid presents a securitythreat. The invention has numerous applications, in particular it can beused for scanning hand carried baggage at airport security check points.

BACKGROUND OF THE INVENTION

Some liquids or combinations of liquids and other compounds may causeenough damage to bring down an aircraft. As no reliable technology-basedsolution currently exists to adequately address this threat, authoritieshave implemented a ban of most liquids, gels and aerosols in cabinbaggage.

As a result, there have been disruptions in operations (e.g., a longerscreening process; changed the focus for screeners; additionalline-ups), major inconveniences for passengers (as well as potentialhealth hazards for some) and economic concerns (e.g., increasedscreening costs; lost revenues for airlines and duty free shops; largequantities of confiscated—including hazardous—merchandise to disposeof), and so on.

Clearly, there is a need to provide a technology-based solution toaddress the threat of fluids that are flammable, explosive or commonlyused as ingredients in explosive or incendiary devices.

SUMMARY OF THE INVENTION

The invention provides a method to perform security screening at anairport on hand-carried baggage. The method includes requestingpassengers with hand carried baggage to remove from the baggage acontainer that holds a liquid and to perform an x-ray inspection on thehand carried baggage and on the container while the container remainsoutside the baggage. The results of the x-ray inspection are used todetermine:

-   -   1. if the baggage contains illegal objects;    -   2. if the liquid is a security threat.

The Invention also provides a security screening system to determine ifa container holding a liquid presents a security threat. The screeningsystem includes an input for receiving image data conveying an image ofthe liquid product generated when the liquid product is subjected topenetrating radiation. The screening system also includes a knowledgebank containing a plurality of entries, each entry containinginformation about one or more liquid characteristics. The screeningsystem further includes a logic module which uses the image data todetermine if the liquid in the container can be matched to anyone of theentries and then uses those results to assess if the liquid poses asecurity threat.

The invention also provides a security screening system to determine ifa container bearing a liquid product identification holds a liquidmatching that product identification. The screening system has aninspection device for acquiring one or more characteristics of thecontainer and for deriving a response of the liquid to penetratingradiation. The system also includes a knowledge bank containingresponses of different commercially available liquids to penetratingradiation, each response mapped to one or more characteristics of acontainer in which the liquid is packaged and sold in the market. Alogic module is also provided for searching the knowledge bank toidentify one or more entries matching the one or more characteristicsacquired by the characterization module and for comparing the responsesof the identified entries to the response of the liquid, the logicmodule using the results of comparing operation to determine if theliquid in the container matches the product identification on thecontainer.

The invention further provides a security screening system to determineif a container bearing a liquid product identification holds a liquidthat poses a security threat. The screening system has acharacterization module to acquire one or more characteristics of thecontainer and an inspection device for subjecting the container topenetrating radiation and for deriving a response of the liquid to thepenetrating radiation. A knowledge bank is also provided containingresponses of different commercially available liquids to penetratingradiation, each response mapped to one or more characteristics of acontainer in which the liquid is packaged and sold in the market. Alogic module searches the knowledge bank to identify one or more entriesmatching the one or more characteristics acquired by thecharacterization module and for comparing the responses of theidentified entries to the response of the liquid, the logic module usingthe results of said comparing to determine if the liquid in thecontainer poses a security threat.

The invention also provides a computer readable medium containing aknowledge bank, the knowledge bank having a plurality of entries, eachentry comprising:

-   -   a) one or more characteristics of a container in which a liquid        is packaged and sold in the market;    -   b) a response of the liquid observed when the liquid is        subjected to penetrating radiation.

The invention further provides a system for determining a parameter of aliquid in a container, the parameter being selected in the groupconsisting of density and effective atomic number. The apparatus havingan input for receiving X-ray image data representing a two-dimensionalX-ray image of the container holding the liquid and a computer basedlogic module for:

-   -   i) processing the X-ray image data to derive path length        information, the path length information being indicative of a        length of a path followed by X-rays through the liquid;    -   ii) using the path length information to determine the        parameter.

The invention further provides a method for determining if a liquidproduct comprised of a container holding a liquid presents a securitythreat. The method includes receiving image data conveying an image ofthe liquid product produced when the liquid product is subjected topenetrating radiation and also providing a knowledge bank storing aplurality of entries, each entry containing information about one ormore liquid characteristics. The method further includes using the imagedata to determine if the liquid in the container can be matched toanyone of the entries and then using the results of the matchingoperation in assessing if the liquid in the container poses a securitythreat.

The invention yet provides a method for determining a parameter of aliquid in a container, the parameter being selected in the groupconsisting of density and effective atomic number. The method includesthe steps of receiving X-ray image data representing a two-dimensionalX-ray image of the container holding the liquid and processing the X-rayimage data with a computer to:

-   -   I) derive path length information, the path length information        being indicative of a length of a path followed by X-rays        through the liquid;    -   ii) determine the parameter by using the path length        information.

The invention further provides a system for determining a parameter of aliquid in a container, the parameter being selected in the groupconsisting of density and effective atomic number. The apparatus has aninput for receiving X-ray image data representing a two-dimensionalX-ray image of the container holding the liquid and a computer basedlogic module for:

-   -   i) processing the X-ray image data to derive container height        information, the container height information being indicative        of a length of a path followed by X-rays through the liquid;    -   ii) using the container height information to determine the        parameter.

The invention also provides system for determining a parameter of aliquid in a container, the parameter being selected in the groupconsisting of density and effective atomic number. The apparatus havingan input for receiving X-ray image data representing a two-dimensionalX-ray image of the container holding the liquid and a computer basedlogic module for:

-   -   i) processing the X-ray image data to derive liquid height        information indicative of a height of the body of liquid held by        the container;    -   ii) using the liquid height information to determine the        parameter.

The invention further provides method for determining a parameter of aliquid in a container, the parameter being selected in the groupconsisting of density and effective atomic number. The method includesthe steps of receiving X-ray image data representing a two-dimensionalX-ray image of the container holding the liquid and processing the X-rayimage data with a computer to:

-   -   i) derive liquid height information indicative of a height of        the body of liquid held by the container;    -   ii) determine the parameter by using the liquid height        information.

The invention also provides a system for determining a parameter of aliquid in a container, the parameter being selected in the groupconsisting of density and effective atomic number. The apparatusincludes an input for receiving X-ray image data representing atwo-dimensional X-ray image of the container holding the liquid, theX-ray image data conveying compound attenuation information indicating adegree with which X-rays are attenuated by the liquid and by thecontainer walls and a computer based logic module for:

-   -   i) processing the X-ray image data to compensate the compound        attenuation information for the attenuation due to the container        walls and derive attenuation information due to the liquid;    -   ii) using the attenuation information due to the liquid to        derive the parameter.

The invention also provides a security screening system to determine ifa liquid product comprised of a container holding a liquid presents asecurity threat. The screening system having an input for receivingimage data conveying an image of the liquid product produced when theliquid product is subjected to penetrating radiation and a display fordisplaying an image of the liquid product generated on the basis of theimage data. The screening system also has a user interface including atleast one user interface tool allowing an operator to perform adesignation on the display of the container, the designation generatinglocation data identifying an area of the image where the containerresides and a logic module to select a portion of the image data on thebasis of the location data and to process the selected image dataportion to determine if the liquid in the container poses a securitythreat.

The invention further provides a security screening system to determineif a liquid product comprised of a container holding a liquid presents asecurity threat. The security screening system including an input forreceiving image data conveying an image of the liquid product producedwhen the liquid product is subjected to penetrating radiation and adisplay for displaying an image of the liquid product generated on thebasis of the image data. The security screening system further includinga logic module to process the image data to determine if the liquid inthe container poses a security threat, the logic module issuing commandsto the display to cause the display to visually enhance a portion of theimage where the container resides to make the container visually moredistinguishable from other objects appearing in the image.

BRIEF DESCRIPTION OF THE DRAWINGS

A detailed description of examples of implementation of the presentinvention is provided hereinbelow with reference to the followingdrawings, in which:

FIG. 1 a is a block diagram of an apparatus using X-rays to scan handcarried baggage at a security check point, according to a non-limitingexample of implementation of the invention;

FIG. 1 b is a more detailed illustration of the X-ray apparatus of FIG.1 a;

FIG. 2 a is a more detailed block diagram of the processing module ofthe apparatus shown in FIG. 1 b;

FIG. 2 b is a generalized block diagram of the process implemented bythe apparatus at FIG. 1 to perform the security screening;

FIG. 3 is a block diagram of the procedure followed by passengers tohave their hand carried baggage screened at the security checkpoint;

FIG. 4 is graph illustrating the total X-ray attenuation in H₂O due tovarious X-ray matter interactions;

FIG. 5 is a generalized illustration of the photoelectric X-rayabsorption process;

FIG. 6 is a generalized illustration of the Compton scattering effect;

FIG. 7 is detailed block diagram of a first non-limiting example of theprocess shown in FIG. 3;

FIG. 8 illustrates an experimental set-up for implementing the methodshown in FIG. 7;

FIG. 9 is an illustration showing the image information derived from theset-up of FIG. 7;

FIG. 10 is an X-ray image of a container holding a liquid, showing aline-like Region Of Interest (ROI) along which grey level values arecalculated;

FIG. 11 is a graph illustrating the grey level profile along the ROI ofFIG. 10;

FIG. 12 is a graph illustrating the grey level profile of a high energy(hi-E) X-ray image of a container holding a liquid, showing that thegrey level profile matches the cross-sectional shape of the container;

FIG. 13 is a graph illustrating the grey level profile of the low energy(low-E) X-ray image of the container shown in FIG. 12, also showing thatthe low-E grey level profile matches the cross-sectional shape of thecontainer;

FIGS. 14 to 18 are graphs illustrating the grey level profiles of hi-EX-ray images of different liquid containers and the correspondingcontainer shapes;

FIG. 19 a is a detailed block diagram of a second non-limiting exampleof implementation of the process shown in FIG. 3;

FIG. 19 b is a table-like representation of a knowledge bank storinginformation about liquid products and their associated threat statuses;

FIG. 20 is a set-up for implementing the method shown in FIG. 19 a;

FIG. 21 is a detailed block diagram of a third non-limiting example ofimplementation of the process shown in FIG. 3;

FIG. 22 is a graph showing the variation of the diffraction/scatteringsignature with molecular density;

FIG. 23 is a flow chart of a process for performing X-ray imageprocessing to remove the contribution in the image of the belt of theX-ray imaging system;

FIG. 24 is a flow chart of a process for performing X-ray imageprocessing to determine in the X-ray image the location and orientationof a tray;

FIG. 25 is a flow chart of a process for performing X-ray imageprocessing to remove the contribution in the image of the tray detectedin FIG. 24;

FIG. 26 is a flowchart of a process for performing a calculation of thedensity and the effective atomic number of a liquid in a X-ray image;

FIG. 27 is a flowchart of a process for performing X-ray imageprocessing to remove the contribution in the image of the wall of acontainer that appears in the image;

FIG. 28 is a flowchart of a process for determining threat assessment ofa liquid;

FIG. 29 is a diagram of an X-ray image scanner illustrating a method tocompute the path length of the X-ray beams through a body of liquid heldinside a container;

FIG. 30 is a simulated x-ray image of two overlapping containers;

FIG. 31 is a flowchart of a process for allowing the operator to specifyon the image at FIG. 30 the container to be analyzed;

FIG. 32 is a simulated X-ray image illustrating the mapping betweenimage portions and individual detectors of the X-ray imaging system.

In the drawings, embodiments of the invention are illustrated by way ofexample. It is to be expressly understood that the description anddrawings are only for purposes of illustration and as an aid tounderstanding, and are not intended to be a definition of the limits ofthe invention.

DETAILED DESCRIPTION

With reference to FIG. 1 a, there is shown a specific non-limitingexample of a system 10 for use in screening containers with liquids, inaccordance with a non-limiting embodiment of the present invention. Thesystem 10 comprises an x-ray apparatus 100 that applies an x-rayscreening process to a liquid 104 (Note that for the purpose of thisspecification “liquid” refers to a state of matter that is neither gasnor solid and that generally takes the shape of the container in whichit is put. This definition would, therefore encompass substances thatare pastes or gels, in addition to substances having a characteristicreadiness to flow. For instance, toothpaste, and other materials havingthe consistency of toothpaste would be considered to fall in thedefinition of “liquid”.) contained in a container 102 that is locatedwithin a screening area of the x-ray apparatus 100. In an airportsetting, a passenger may place the container 102 in a tray 106 which isthen placed onto a conveyor 114 that causes the container 102 to enterthe screening area of the x-ray apparatus 100. The x-ray apparatus 100outputs an image signal 116 to a processing module 200.

The processing module 200 may be co-located with the x-ray apparatus 100or it may be remote from the x-ray apparatus 100 and connected theretoby a communication link, which may be wireless, wired, optical, etc. Theprocessing module 200 receives the image signal 116 and executes amethod (to be described later on) to produce a threat assessment 118.The processing module 200 has access to a database 400 which constitutesa knowledge bank via a communication link 120 that may be local to theprocessing module 200 (e.g., on a common printed circuit board, orconnected as a peripheral device thereto by cable or Bluetooth), orwhich can be remote from the processing module 200 (e.g., connected viaa wireline, wireless or optical link that may traverse a data network).The processing module 200 may be implemented using software, hardware,control logic or a combination thereof.

The threat assessment 118 is provided to a console 350 and/or to asecurity station 500, where the threat assessment 118 can be conveyed toan operator 130 or other security personnel. The console 350 can beembodied as a piece of equipment that is in proximity to the x-rayapparatus 100, while the security station 500 can be embodied as a pieceof equipment that is remote from the x-ray apparatus 100. The console350 may be connected to the security station 500 via a communicationlink 124 that may traverse a data network (not shown).

The console 350 and/or the security station 500 may comprise suitablesoftware and/or hardware and/or control logic to implement a graphicaluser interface (GUI) for permitting interaction with the operator 130.Consequently, the console 350 and/or the security station 500 mayprovide a control link 122 to the x-ray apparatus 100, thereby allowingthe operator 130 to control motion (e.g., forward/backward and speed) ofthe conveyor 114 and, as a result, to control the position of thecontainer 102 within the screening area of the x-ray apparatus 100.

In accordance with a specific non-limiting embodiment, and withreference to FIG. 1 b, the x-ray apparatus 100 is a dual-energy x-rayapparatus 100A. However, persons skilled in the art will appreciate thatthe present invention is not limited to such an embodiment. Continuingwith the description of the dual-energy x-ray apparatus 100A, an x-raysource 202 emits x-rays 206 at two distinct photon energy levels, eithersimultaneously or in sequence. Example energy levels include 50 keV (50thousand electron-volts) and 150 keV, although persons skilled in theart will appreciate that other energy levels are possible.

Generally speaking, x-rays are typically defined as electromagneticradiation having wavelengths that lie within a range of 0.001 to 10 nm(nanometers) corresponding to photon energies of 120 eV to 1.2 MeV.Although the electromagnetic radiation referred to primarily throughoutthis description are x-rays, those skilled in the art will appreciatethat the present invention is also applicable to electromagneticradiation having wavelengths (and corresponding photon energies) outsidethis range.

A detector 218 located generally along an extension of the path of thex-rays 206 receives photons emanating from the combination of the liquid104 and the container 102 in which it is located. Some of the incomingphotons (X-rays 206) will go straight through the container/liquid 104combination while some will interact with the container/liquid 104combination. There are a number of interactions possible, such as:

-   -   The Rayleigh scattering (coherent scattering)    -   The photoelectric absorption (incoherent scattering)    -   The Compton scattering (incoherent scattering)    -   The pair production;    -   Diffraction

The total attenuation of the contribution of the various X-rays—matterinteractions is shown in FIG. 4. In this example the matter is H₂O butthe attenuation profile for other materials is generally similar. Fortoday's state-of-the-art security screening systems, the energy levelscommonly utilized lie between 50 keV and 150 keV.

The photoelectric absorption (FIG. 5) of X-rays occurs when the X-rayphoton is absorbed, resulting in the ejection of electrons from theshells of the atom, and hence the ionization of the atom. Subsequently,the ionized atom returns to the neutral state with the emission ofwhether an Auger electron or an X-ray characteristic of the atom. Thissubsequent X-ray emission of lower energy photons is however generallyabsorbed and does not contribute to (or hinder) the image makingprocess. This type of X-ray interaction is dependent on the effectiveatomic number of the material or atom and is dominant for atoms of highatomic numbers. Photoelectron absorption is the dominant process forX-ray absorption up to energies of about 25 keV. Nevertheless, in theenergy range of interest for security applications, the photoelectriceffect plays a smaller role with respect to the Compton scattering,which becomes dominant.

Compton scattering (FIG. 6) occurs when the incident X-ray photon isdeflected from its original path by an interaction with an electron. Theelectron gains energy and is ejected from its orbital position. TheX-ray photon looses energy due to the interaction but continues totravel through the material along an altered path. Since the scatteredX-ray photon has less energy, consequently it has a longer wavelengththan the incident photon. The event is also known as incoherentscattering, because the photon energy change resulting from aninteraction is not always orderly and consistent. The energy shiftdepends on the angle of scattering and not on the nature of thescattering medium. Compton scattering is proportional to materialdensity and the probability of it occurring increases as the incidentphoton energy increases.

The diffraction phenomenon of the x-rays by a material with which theyinteract is related to the scattering effect described earlier. When thex-rays are scattered by the individual atoms of the material, thescattered x-rays may then interact and produce diffraction patterns thatdepend upon the internal structure of the material that is beingexamined.

The photons received by the detector 218 include photons that have gonestraight through the liquid 104 and the container 102; these photonshave not interacted in any significant matter with the liquid 104.Others of the received photons have interacted with the liquid 104 orthe container:

In accordance with a specific non-limiting embodiment of the presentinvention, the detector 218 may comprise a low-energy scintillator 208and a high-energy scintillator 210, which can be made of differentmaterials. The low-energy scintillator 208 amplifies the intensity ofthe received photons such that a first photodiode array 212 can producea low-energy image 220. Similarly, the high-energy scintillator 210amplifies the intensity of the received photons such that a secondphotodiode array 214 can produce a high-energy image 222. The low-energyimage 220 and the high-energy image 222 may be produced simultaneouslyor in sequence. Together, the low-energy image 220 and the high-energyimage 222 form the aforesaid image signal 116.

Referring back to FIG. 1 a, the processing module 200 receives the imagesignal 116 and processes the signal in conjunction with data containedin a knowledge bank 400 to determine if the liquid in the containerposes a security threat. The determination can include an explicitassessment as to whether the liquid is a threat or not a threat.Alternatively, the determination can be an identification of the liquidor the class of materials to which the liquid belongs, withoutexplicitly saying whether the liquid is threatening or not threatening.For example, the processing module can determine that the liquid is“water”, hence the operator 130 would conclude that it is safe. In adifferent example, the processing module 200 determines that the liquidbelongs to a class of flammable materials, in which case the operator130 would conclude that it would be a security threat. Also, thedetermination can be such as to provide an explicit threat assessmentand at the same time also provide an identification of the liquid interms of general class of materials or in terms of a specific material.The results of the determination are conveyed in the threat assessmentsignal 118 which is communicated to the console 350 and/or the securitystation 500 where it is conveyed to the operator 130.

FIG. 2 a is a high level block diagram of the processing module 200. Theprocessing module 200 has a Central Processing Unit (CPU) 300 thatcommunicates with a memory 302 over a data bus 304. The memory 302stores the software that is executed by the CPU 300 and which definesthe functionality of the processing module 200. The CPU 300 exchangesdata with external devices through an Input/Output (I/O) interface 306.Specifically, the image signal 116 is received at the I/O interface 306and the data contained in the signal is processed by the CPU 300. Thethreat assessment signal 118 that is generated by the CPU 300 is outputto the console 350 and/or the security station 500 via the I/O interface306. Also, communications between the knowledge bank 400 and theprocessing module 200 are made via the I/O interface 306.

FIG. 2 b is a high level block diagram that illustrates the functionsperformed by the processing module 200 in assessing whether or not theliquid in the container presents a security risk. This block diagramapplies to, the example of implementation shown at FIG. 1 a and also toother examples of implementation that will be described later. The firststep of the process, illustrated at 400 is to perform a characterizationof the product that is being screened. By “product” is meant thecombination container and liquid inside. The characterization stepreturns information conveying distinctive features of the product thatallows distinguishing the product from other products. Thecharacterization step is performed on the container but it may alsoinclude the liquid inside. For instance the characterization step 401may return information such as the general shape of the container, itsheight, cross-sectional profile and width among many other parameters.Characterization of the liquid is optional and may provide informationsuch as the color of the liquid (assuming of course the container istransparent).

The characterization step 401 can be performed by using different typesof equipment capable to capture the distinctive features of the product.One example is an apparatus using penetrating radiation such as theX-ray imaging system 100 of FIG. 1 a. This is convenient since the sameapparatus can be used to characterize the product and also obtain theresponse of the liquid in the container to X-rays. Yet another exampleis to use a device that will obtain an image of the product and performthe characterization based on that image. The image may be twodimensional or three dimensional. Yet another possibility is to useequipment to read machine readable labels or tags on the container. Thereading can be done optically or via radio frequency (RF) informationcapture.

The characterization step of the product is followed by a determinationof the response of the liquid in the container to X-rays, as shown atstep 402. The response represents the interaction of the liquid with theX-rays as discussed above. The response can be expressed in termsparameters characterizing the liquid. Examples of parameters include:

-   -   The density of the liquid;    -   The effective atomic number of the liquid (Z_(eff));    -   The diffraction/scattering signature    -   The viscosity of the liquid

At step 404, a knowledge bank is searched on the basis of the productcharacterization performed at step 401. In the vast majority of cases,the screening process described in FIG. 2 b will be performed oncommercially available products such as water bottles, juices, softdrinks, personal hygiene items such as toothpaste, shampoo, lotions,etc. The knowledge bank contains characterization data for a number ofthose commercially available products and the associated responses toX-rays of the genuine liquids in the containers. So, step 404 searchesthe knowledge bank to locate one or more entries that match the productcharacterization derived at step 401. If one or more entries are foundthat match the product characterization, the corresponding responses toX-rays are extracted from the knowledge bank and compared to theresponse obtained at step 402. If the response extracted from theknowledge bank 400 matches the response obtained at step 402 then theprocess concludes that the product that is being screened is a genuineproduct, in other words the liquid inside matches the commercialidentification on the container. On the other hand, if no match isfound, such as when the response to X-rays derived at step 402 does, notmatch any of the responses associated with the one or more entriesextracted from the knowledge bank 400, this constitutes a goodindication that the original liquid in the container has beensubstituted with a different liquid.

The process determines at step 406 a threat assessment on the basis ofthe knowledge bank search. The threat assessment conveys informationindicating if the product is a security risk. Any container that holdsliquid which is other than the commercial labelling on the container isconsidered suspect. Although there may be perfectly legitimate cases (awater bottle filled with juice) those instances are still flagged assecurity threats to provide the security personnel at the check point toInvestigate further.

Note that the mere fact that a product can be matched to an entry in theknowledge bank 400 does not per se indicate that the product is safe.While the knowledge bank 400 contains a large number of referenceinformation for safe and legitimate products, it may also containreference entries for prohibited products. If a product can be matchedto an entry for a prohibited product then an “unsafe” threat assessmentwill issue. For instance, if a container labelled as holding acid oranother corrosive or flammable substance is scanned, it will beconsidered as a threat irrespective of the results of the knowledge banksearch. If a match is found then it means that the liquid in thecontainer has not been substituted with something else but since theliquid is prohibited then the assessment triggers a security alert. Onthe other hand, if no match can be established then the product isconsidered suspect because the original liquid may have been substitutedwith something else.

In the above examples, the knowledge bank 400 provides a threat statusreference. If a match is found with an entry in the knowledge bank 400,then the threat status of the product can be derived on the basis of thethreat status of the entry. In a possible variant, the knowledge bank400 is designed in a way as to provide no threat status Informationdirectly or indirectly on the entries it contains. In this instance,when a match between a product that is being scanned and an entry in theknowledge bank 400 would, therefore, indicate that the response of theliquid in the container, as determined by the processing module 200 isessentially correct. Those correct measurements therefore can be used asa sound basis for further processing or assessment to derive the threatstatus of the product. For example, the response of the liquid to x-raysis used to determine the density of the liquid and its effective atomicnumber. If a match in the knowledge bank 400 has been found, this meansthat the determined density and effective atomic number values have beenvalidated and can be relied upon to perform the threat statusassessment. The actual threat status assessment can be done on the basisof a combination of those values; certain combinations can be associatedwith dangerous materials while certain others with safe materials.

In the instance where the step 404 fails to find a match between theproduct and an entry in the knowledge bank 400, the option exists toassume that the product is a security threat since no reference to anentry is possible that has a known security threat status or at leastone that can validate the response of the liquid determined by theprocessing module 200. Another possibility is to continue the processingand rely nevertheless on the response of the liquid as determined by theprocessing module 200 to provide a threat assessment.

FIG. 3 is a flowchart of the method that is implemented at a securitycheckpoint at an airport or any other suitable location to screen handcarried baggage that relies on one example of implementation of theliquid screening process described earlier. The security checkpointwhere this method is implemented would use an X-ray imaging system ofthe type shown in FIG. 1 a for example. At step 501 the passengerapproaching the checkpoint is requested by security personnel or showndirectives appearing on a board or any suitable display to remove anycontainers holding liquids that may be present in the hand carriedbaggage. At step 502 the containers are placed in a tray and put on theconveyor belt of the X-ray imaging system. The hand carried baggage issimilarly put on the conveyor belt of the X-ray imaging system. Thecontainers and the hand carried baggage are therefore separately scannedbut in a′serial fashion by the same X-ray imaging system. At step 504the operator of the X-ray imaging system examines the X-ray image thatis generated as a result of the X-ray scan to determine if it containsillegal objects. At step 506 the containers in the tray are scanned andthe image signal 116 is processed by the processing station 200 todetermine if anyone of the liquids poses a security threat. If nosecurity threat is found then the passenger is permitted to put thecontainers back in the hand carried baggage and to proceed beyond thecheckpoint.

FIG. 7 is a more detailed flowchart of the process for performing asecurity screening on a container holding a liquid, according to a firstnon-limiting example of implementation. The process uses X-ray scanningto perform the characterization of the product (container+liquid) andalso to determine the response of the liquid to X-rays. In other words asingle X-ray scan is used to extract both pieces of information. Oneexample of an X-ray imaging system that can be used for this purpose isthe equipment manufactured by Gilardoni in Italy, model number FEP ME640 DETEX. This machine is a dual energy device that produces X-rays athigh and low energy values that are HI (high)=74.298 keV and Lo(low)=55.398 keV, respectively.

FIG. 8 illustrates the general configuration of the X-ray imagingsystem. The machine 800 has a conveyor belt 802 on which items to bescanned are placed. The X-ray source 804 is located below the conveyorbelt 802. Detector arrays 806, 808 are placed on the vertical and thehorizontal walls of the casing. For clarity, when the conveyor belt 802advances the container through the x-ray machine 800, the direction ofmovement would follow an imaginary line that would be perpendicular tothe sheet of the drawing.

A container that is being scanned in shown at 810. In this example, thecontainer is a 1.3 mm thick polypropylene bottle filled with liquid.

Referring back to the flowchart of FIG. 7, the process starts at step702 where the container is placed in a tray (not shown in FIG. 8 forclarity) and then placed on the conveyor belt 802. The X-ray scan isthen performed. At step 702 the processing module 200 (FIG. 1 a)acquires the image information 116. In this particular example, theimage information 116 is the raw data file output by the X-ray imagingsystem. The raw data file is then converted at step 706 into distinctimage files. This is best shown at FIG. 9. The raw data file exportedfrom the X-ray imaging system is converted into three separate imagefiles, namely HI, Lo and class data. The HI file represents the X-rayattenuation at the HI energy level. The Lo file represents the X-rayattenuation at the Lo level. Finally, the class data file is thematerial classification image that uses colors to illustrate thematerials from which the objects shown in the image are made. Class datafiles are generated by the X-ray imaging system directly and they arenormally displayed on the monitor of the X-ray imaging system. In thisparticular example the class data information is not being used, howeverone can certainly envisage integrating the class data information to theprocessing to further refine the results of the security assessment.

The HI and the Lo files are grey level image files showing X-rayenergies quantified in a number of different levels. The number of greylevels used can vary depending upon the desired resolution; usually thehigher the number of grey levels used the better the precision will be.Test conducted with images encoded at 256 grey levels (each pixel isrepresented by an 8 bit value) have demonstrated that the process works,however the error resulting from the loss of information due to thefairly coarse encoding is not negligible. Therefore, grey levels inexcess of 256 would be preferred. However, images encoded at less than256 grey levels can still be uses for some specific applications thatrequire a lesser degree of detection detail.

Referring back to FIG. 7, the image files HI and Lo are then subjectedto two parallel processing threads, 710 and 712 that determinerespectively, the density and effective atomic number of the liquid andcharacterize the product. Note that these threads are not independent.The results of the processing thread 712 are supplied to the processingthread 710, such that the density and effective number computations cantake into account the X-rays attenuation resulting from the presence ofthe container.

The processing thread 712 starts at step 714 where an edge detection ofthe container is performed. The purpose is to derive from theinformation in the HI, Lo image files the location and characteristicsof the container. FIGS. 10 and 11 illustrate the general principle ofthe edge detection process. Consider in FIG. 10 the X-ray image of thecontainer 1000 (Lo image information). FIG. 11 shows the grey levelprofile in the image taken along the imaginary line 1002 drawn acrossthe container 1000. The areas 1004 and 1006 in FIG. 11 correspond toareas along the line 1002 that are outside the container 1000. The zone1008 corresponds to the location of the container. It can be observedthat the shape of the grey level profile curve matches quite preciselythe cross-sectional shape of the container 1000. FIGS. 12 to 18 provideadditional examples. FIG. 12 is the HI image of a container and theassociated grey level profile curve. FIG. 13 shows the grey level curveof the corresponding HI image. In both cases, the curves match thegenerally rectangular cross-sectional profile of the container.Specifically, the Inflection points 1202 and 1204 correspond to thecontainer edges 1206 and 1208, respectively. The flat region 1210between the inflection points 1202 and 1204 corresponds to the flat topsurface 1212 of the container.

FIGS. 14, 15, 16 and 17 show examples of grey level profiles ofcontainers having rounded features. FIGS. 14, 16 and 17 clearly showthat the grey scale profile matches the rounded cross-sectional contourof the bottle.

FIG. 18 is the grey level, profile along the container (from top tobottom). Again the profile shows characteristic features of thecontainer. In particular, the area 1802 of the curve corresponds to thebottom portion of the container, the area 1804 shows the tap of thecontainer, the area 1806 reveals the notch below the cap and thedepression 1808 corresponds to the waist in the middle of the container.

Referring back to FIG. 7, the edge detection process 714, thereforeperforms an analysis of the HI and the La image data to detect the edgesof the container. Assume for the sake of this example that the containerlies horizontally in the tray as it is being scanned by the x-raymachine. Accordingly, the grey level image produced by the x-ray machinewill resemble a plan view of the container. The software executed by theprocessing module 200 which performs the edge detection process appliesthe following logic:

-   -   1. The first step is to locate a portion of the edge. The        software searches for detectable grey level transition that        occurs in the image as a result of the container wall.        Specifically, due to the structure/material of the container        wall a well defined grey level transition will show in the        image. To facilitate the edge detection process it is possible        to provide the operator console 350 with user interface tools        that will allow the operator to designate in the X-ray image the        general area where the container is located. In this fashion,        the software will start the image analysis in an area of the        image that is known to contain the image of a container.        Specifically, the user interface on the console 350 is designed        such as to display to the operator 130 the X-ray image obtained        as a result of the scanning operation. The X-ray image displayed        may be the derived from the HI image data, the Lo image data or        a combination thereof. Once the image is shown to the operator        130, he or she uses a tool to indicate where a container lies.        FIG. 30 shows an example of such x-ray image where several        containers appear at once. Specifically this image shows two        containers 3100 and 3102 that are partially on top of each        other. This may arise when they have been placed in the tray        hastily, which is likely to occur in practice quite often.    -    The operator 130 first identifies the container to be        processed. Assume that this is container 3100. The operator 130        then uses a user interface tool to designate the container 3100        to the software. The tool may be any suitable user interface        tool such as pointer device such as a mouse or a touch sensitive        feature allowing the operator 130 to touch the screen at the        area of interest. When the pointer device is activated at the        location 3104, which by convention is deemed to correspond        generally to the centre of the container 3100, the activation        will produce location data. The location data identifies an area        in the image where the container 3100 resides. The software uses        the location data to select the portion of the image data to        which the location data points to and starts the image analysis        in that area. The selected area corresponds to the location        3104. The software operates with the assumption that the        container features that will be identified should have some        degree of symmetry about that location. The software scans the        image data by moving further away from the location 3104 until a        sharp grey level gradient is located that corresponds to a        container edge. In principle since the location 3104 is in the        centre of the container then a container edge should be detected        in the image at two places equally spaced from the location        3104.    -    Another possibility is for the operator to designate with the        pointing device specifically the edge of the container that is        to be analysed. For Instance the operator 130 “clicks” the mouse        or touches the screen with his/her finger at the location 3106        that corresponds to the edge of the container 3100.    -    Yet another possibility is for the operator to perform the        designation by “drawing” on the image a zone curtailing the area        where the container 3100 is located. For instance the operator        130 can use the pointing device to draw the line 3108 around the        container 3100.    -    With any one of the methods described earlier, the edge        detection software receives operator guidance to perform an        image analysis and extract from the image one or more        characterizing features of the container 3100.    -    FIG. 31 provides a flowchart that that summarizes the above        process. At step 3200 the image of the one or more containers is        shown on the console 350 of the operator. At step 3202 the        operator uses a suitable user interface tool to designate the        container to be analyzed. As indicated earlier, the user        interface tool may be a pointing device, among others. At step        3204 information about the location in the image where the        container is located is communicated to the processing module        200 such that the container analysis can be performed.    -   2. Referring back to FIG. 30, the next step of the process is to        track the outline of the container 3100. As the software has        identified a portion of the container's edge, the software logic        then starts tracking that edge. The tracking logic tracks the        sharp grey level gradient in the image to follow the container        edge. In doing so, the tracking logic uses a set of assumptions;        otherwise it may stray, in particular at areas where two or more        container edges meet. This is shown in the area 3110 where the        edges of the two different containers 3100 and 3102 intersect        each other. If the tracking software is moving along the edge        3112 (in the direction shown by the arrow) it will eventually        encounter the location 3114 where the edges of the two        containers 3100 and 3102 cross each other. At that location, the        edge tracking software has at least three different edges that        it can track, namely edge portion 3116, 3118 and 3120, while        only one solution (edge 3120 is valid). To avoid straying along        the non-valid solutions (edges 3118 and 3116) one of the        assumptions is that the edge of the container has no sharp edges        or turns. A sharp edge or turn is defined by a radius value,        which is a parameter that can be permanently set or made        adjustable. Accordingly, when the tracking software reaches the        location 3114 the solutions that correspond to edge portions        3118 and 3116 are rejected because they involve a sharp        departure from the existing course (edge portion 3112). Then        only solution 3120 remains as valid.    -    Other assumptions can also be used. One is the container        symmetry attribute. Most of the containers are symmetrical about        one or more axes. When one side of the container wall has been        tracked the other side should in principle be a mirror image of        the first side, accordingly only solutions that correspond to        that mirror image path would be retained. Another assumption is        the maximal or minimal dimension of the container or of its        constituent parts. For instance, it is known that containers        typically have dimensions that do not exceed a certain limit        that is considered to be a maximal value. Accordingly if an edge        length extends beyond those limits the detection process may be        considered invalid. Similarly, minimal dimensions can also be        taken into consideration. If an edge length is below a value        that is considered to be a minimum for a container height or        width, the detection process may be considered invalid.    -   3. When the tracking logic has completed the identification of        the container edge, then the software performs a validation on        the basis of the overall container shape defined. Specifically        the software will compute certain geometric features or        properties of the container and determine if they fall into        acceptable acceptance windows. Examples of such geometric        features include:        -   The height of the container. Usually, most containers would            have a height that would fall in a certain range, say from 3            inches up to 18 inches. Any container height dimension            outside that range should be suspect.        -   The width of the container. As in the case with the            container height, the container width usually falls in a            certain range, for instance between 1 inch and 6 inches.            Containers having a width outside that range would also be,            suspect.        -   The ratio height/width which is considered to be valid only            if the value computed falls in a predetermined range.        -   A volume prediction of the container. On the basis of the            container outline one can predict what the internal volume            could be. While to perform an accurate volume computation            the actual thickness (3^(rd) dimension) of the container is            required, that dimension can be assumed in order to provide            volume estimation. The container thickness would normally be            in the range of 1 inch to 6 inches. This allows providing a            volume estimation that defines a window allowing rejecting            solutions associated with volume values that are outside the            window.    -   4. When the container validation process has been completed, the        outline of the container can be emphasised to the operator 130,        as a final “sanity check”. This step is identified at block 716        of FIG. 7. Specifically, the processing module 200 issues        commands to the display such that the display visually enhances        a portion of the image where the container is located. This        makes the container more visible with relation to other objects        in the x-ray image. Examples image enhancements include:        -   a. Colouring or otherwise highlighting the areas of the            image that correspond to the portions where the edge has            been identified;        -   b. Colouring or otherwise highlighting the container in its            entirety;        -   c. De-emphasising the image except the areas where the            container lies. This technique does not change the pixels of            the x-ray image in the region of the container but changes            all the pixels that surround the container image such as to            make the container more visible.    -    The highlighting process uses the edge detection data obtained        by the edge detection software as a result of the x-ray image        analysis. The edge detection data defines in the x-ray image the        areas where an edge has been identified. The highlighting        process then uses this information to manipulate the x-ray image        pixels such that the container stands out with relation to its        surroundings.    -    If the edge identification has been done correctly the operator        130 would see the container 3100 highlighted. The operator 130        can then apply human judgment on the results. If the edge        tracking operation is correct then the results can be accepted        and the processing allowed continuing. Otherwise, if the        operator 130 sees on the screen a highlighted shape that does        not correspond to a container then he/she aborts the operation.

At step 718 the edge detection data obtained by the edge detectionsoftware is processed to extract one or preferably more that onecharacteristics of the container. Examples of characteristics include:

-   -   The height of the container    -   The maximal transverse dimension of the container;    -   Wall thickness    -   Generalized geometric shapes that are found in the container.        -   The geometric shape Identification is a software processing            of the container image to try to identify in that image            geometric features or shapes that can be used to            characterize the container. For example, the software may            look at the main body of the container (disregard the neck            portion) to determine if the container falls in any one of a            set of predefined geometric shapes. Examples of geometric            shapes include:            -   rectangular container;            -   square container;            -   upwardly tapered container;            -   downwardly tapered container.

At step 720 the knowledge bank 400 is searched on the basis of thecharacteristics of the container identified previously. The knowledgebank 400 is designed as a database that has a number of entries, eachentry being associated with a product that a passenger is susceptible tocarry in his/her baggage at a security checkpoint where the process ofFIG. 7 is being implemented. Each entry includes two different classesof information. The first class is characterization information aboutthe product. The characterization Information includes one or morefeatures of the container in which the liquid, is stored. Examples offeatures include:

-   -   Container height;    -   Wall thickness;    -   The transverse dimension of the container;    -   Geometric shapes found in the container or the set of predefined        geometric shapes to which the container belongs;    -   Generic container templates;    -   Physical parameters of the container;    -   Chemical parameters of the container such as the material from        which the container is made;    -   Height off belt;    -   Path length calculation parameters (see description later for        path length calculation);    -   Contour details.

In addition the characterization information may also includeinformation about the liquid (other than its response to X-rays), suchas the color of the liquid, smell or visual texture, among others. Underthe current example, the characterization information includes solelyinformation about the container.

The second class includes the responses of liquids (the genuineproducts) that are sold or commercially made available in the containershaving the characteristics stored in the knowledge bank 400. In thespecific example of implementation discussed here, the penetrationradiation used to obtain a response from the liquid is X-rays, however,other types of electromagnetic radiation can be used without departingfrom the spirit of the invention. The information stored in theknowledge bank 400 that characterizes the response to the liquid toX-rays includes density and effective atomic numbers for each liquid.This is useful for applications where the X-ray imaging system onlyprovides an image output obtained on the basis of photons that havepassed straight through the sample. For X-ray imaging systems where theimage output also takes into account scattering/diffraction then theknowledge bank 400 can also include the diffraction/scattering signatureof the liquid.

FIG. 22 shows a graph of the diffraction/scattering signature for anumber of different materials, in particular propanol, acetone, methanoland hydrogen peroxide. The visible texture of the scattering/diffractionsignature changes with the density of the materials and constitutes afeature that can distinguish the different materials. In this example,all the materials shown are flammable, hence “illegal” for transport inthe hand carried baggage aboard an aircraft.

Accordingly, the knowledge bank can be augmented by storing inassociation with each entry the diffraction/scattering signature of theliquid. The diffraction/scattering signature can be in the form of animage file or under any other suitable representation that would allow acomparison to be made with the diffraction/signature of a material thatis being scanned such as to determine if both signatures match.

The diffraction/scattering signature can be used alone to determine if aliquid matches an entry in the knowledge bank, but preferably it can beused in conjunction with the other elements of information that definethe response of the liquid to X-rays, such as density and effectiveatomic number.

Typically, a neural network would be used to determine if the observeddiffraction/scattering signature of a liquid matches anyone of thesignatures stored in the knowledge bank 400.

Assuming now that the knowledge bank search is successful and a uniqueand unmistakable match is found on the basis of the productcharacterization information provided, then the search will extract thenominal container height (step 722) and the nominal wall thickness (724)of the container from the knowledge bank 400. The read container heightand wall thickness are communicated to a processing block 726 whichcomputes the X-ray path length of the container that is being scanned bythe X-ray apparatus. This processing block will be discussed in greaterdetail later.

On the other hand, if no match is found in the knowledge bank 400, thenthe processing continues at step 740 where a height estimation isperformed for the container. In this case, the container height datagenerated during the container characterization step 718 is read andthat information is used as container height information. Similarly, atstep 736 an estimate of the container wall thickness is produced fromthe edge detection data obtained at the edge detection process. Both theestimated edge thickness and container height are then supplied to theblock, 726 which performs the X-ray path length computation. The x-raypath length analysis will be described in greater detail later.

The processing thread 710 that runs in parallel with the processingthread 712 performs image processing in order to identify the responseof the liquid in the container that is being scanned to X-rays. Thefirst step of the process (step 728) is to locate in the HI and Loimages the tray in which the container is placed for the scanningprocess. Since the tray signature is known, known image processingtechniques can be used to identify the location of the tray in theimages and its orientation. The tray signature resides in the memory 302of the processing module 200.

The flowchart of FIG. 24 shows in greater detail the process foridentifying the location and the orientation of the tray in the HI andLo images. To make the identification of the tray simpler, the tray isprovided with a marker that is highly visible to X-rays. This may be apiece of metal that will highly attenuate X-rays, which is located at aknown position in the tray. Therefore, the detection of the trayposition in the image starts by determining where in the HI and the Loimages that marker can be found. For easier identification, the makercan be of an easily recognizable shape unlikely to be confused withother objects placed in the tray during the X-ray scanning process.

At step 2400 the process receives the HI and the Lo image information.The HI image is scanned at 2402 to locate the marker. The image issearched using any well known image scanning techniques on the basis ofthe marker signature at the HI energy level extracted from the memory302 of the processing module 200. If the marker is found, itscoordinates are recorded. The same process is repeated at step 2404,this time on the Lo image. The coordinates of the marker are alsogenerated.

At step 2406 the tray position and contour is determined by processingboth sets of marker coordinates. Since the position of the marker in thetray is known and the shape of the tray is also known, then step 2406will determine the location of the tray in the HI and to images, itscontour and its orientation. The process outputs at step 2408 data thatdefines the location of the tray, its contour and its orientation inboth images. The location, contour and orientation should be such as toallow identifying in each image the pixels “overlaid” by the tray, inother words the pixels whose grey levels include the contribution of thetray to the overall X-ray attenuation.

A somewhat similar operation is performed at step 730 on the HI and Loimages to remove the contribution from the belt 802 (FIG. 8). The belt802 attenuates to a known degree the X-ray radiation and step 730compensates the images accordingly. This is done by modifying the greylevels of the pixels in the HI and the Lo images to produce acompensated image that will show a lesser degree of attenuation. Thedetailed process for removing the contribution of the belt 802 is shownby the flowchart of FIG. 23. Step 2300 receives the HI, and the Loimages information. At step 2302 the signature of the belt 802 for theHI energy level is read from the memory 302 of the processing module200. A search is made in the image such as align or “overlay” the readsignature with the signature appearing in the image. A similar operationis performed at step 2304 for the Lo image. Steps 2306 and 2308compensate the HI and Lo images such as to remove the effect of the belt802. The compensation is done only in the areas of the Hi and La imagesthat are encompassed within the belt signature, hence the areas wherethe gray levels convey attenuation information due to the belt 802presence (the attenuation due to the belt 802 is stored in the memory302). The compensation is done by changing the grey levels to remove theattenuation due to the belt. Since the belt 802 is a relatively uniformstructure, the compensation that is made on the HI and the Lo imagesconsists of reducing the grey level intensity in each pixel by a valuethat corresponds to the attenuation caused by the belt 802. Accordingly,steps 2306 and 2308 produce synthetic HI and Lo images in which theeffect of the belt 802 is removed.

The HI and Lo synthetic images are processed at step 732 (FIG. 7) toremove the contribution of the tray. The details of the tray removal areshown in the flowchart of FIG. 25. The HI and the Lo synthetic images aswell as the data that defines the location of the tray (obtained fromthe process at FIG. 24) are received by the process at step 2500. Step2502 processes the data that defines the location of the tray for the HIand the Lo levels in conjunction with the tray X-ray signature at the HIand Lo levels. The X-ray signature for the HI and the Lo levels isextracted from the memory 302. The processing at step 2502 modifies thesignature extracted from the memory 302 such as to shift it to thecurrent tray location. In other words, the X-ray signature of the traythat is stored in the memory 302 corresponds to a certain reference traylocation. To be able to use this signature in cases where the tray is ina position other than the reference position, then the signature must bemanipulated such as to displace the grey level features that define thesignature to the positions where the tray is actually located. Step 2502performs this operation by using any suitable image processingtechniques that translate and/or rotate the pixels that convey the X-rayattenuation caused by the tray in the actual tray position that waspreviously determined. This produces a real tray signature, for both HIand Lo energy levels that can be used subsequently to compensate the HIand the Lo images for the presence of the tray.

Step 2504 performs the tray removal operation. The process at step 2504receives the synthetic Hi and La images (compensated for the belt) andalso the real tray signature generated earlier. The real tray signaturefor each energy level is “subtracted” from the corresponding syntheticimage such as to remove from the synthetic image the X-ray attenuationinformation resulting from the tray.

Step 2506 outputs the HI and Lo synthetic images that have been cleanedto remove the effects of the belt and the tray.

Referring back to FIG. 7, step 734 further modifies the HI and the Loimages received from the process at step 732 to remove from the imageinformation the attenuation due to the container wall. The material fromwhich the container is made will determine the extent to which thecontainer wall removal is critical. For glass materials it is necessaryto remove their contribution since glass materials tend to attenuateX-ray significantly as in practice they are quite thick. On the otherhand, when the container is made of plastic that attenuates X-rays to amuch lesser degree, the compensation of the image is not absolutelyrequired. The same also holds true for thin walled metallic containers,such as aluminium beverage cans.

The step 734 receives the HI and the Lo images compensated for thepresence of the belt and of the tray, information that approximates thewall thickness of the container (the approximation will be describedlater), real wall thickness information and material of containerextracted from the knowledge bank 400 as output at step 724 (If a matchin the knowledge bank 400 has been found) and the coordinates of thecontainer contour from the edge detection process 714. If the product(container+liquid) that is being scanned has been accurately recognizedat step 720 (a match exists in the knowledge bank 400), then theapproximation of the wall thickness is not required. The wall thicknessapproximation is used only if the product recognition process at step720 is uncertain or has failed. The flowchart at FIG. 27 illustrates ingreater detail the process for compensating the HI and the Lo images forthe attenuation resulting from the container walls.

Step 2800 is the start of the process. That step receives the followinginformation:

-   -   1. HI and Lo images compensated for the attenuation by the belt        and tray;    -   2. Coordinates of the container contour. This information is        received from the processing at step 714 (edge detection). This        information specifies the outline of the container and defines        the area of the HI and Lo images that will need to be        compensated to remove the effect of the container wall.    -   3. The estimated wall thickness;    -   4. The real wall thickness and the material from which the        container is made (information obtained from step 724, if        available).

If only a wall thickness estimation is available (no real wall thicknessinformation found) then the process proceeds at step 2802 that computesthe attenuation brought by the container. Since at that point noknowledge exists about the material from which the container is made,the process at step 2802 assumes that the material is glass, which inmost practical cases would be the worst case scenario (the greatestdegree of attenuation). The step 2802, therefore computes theattenuation that the glass material of the estimated thickness willcreate such that the HI and Lo images can be compensated accordingly.The process performed at step 2802 is a computational step that uses thefollowing algorithm for HI energy level image:

  Bottle_Contr? = MAX_(GS)⌊⌊1 − ?⌋ × 100%⌋?indicates text missing or illegible when filed

and the following algorithm for the Lo energy level image:

  Bottle_Contr? = MAX_(GS)⌊⌊1 − ?⌋ × 100%⌋?indicates text missing or illegible when filed

Where:

-   -   Bottle_Contr.Hi is the container wall attenuation at the Hi        energy level expressed in percentage;    -   Bottle_Contr.Lo is the container wall attenuation at the La        energy level expressed in percentage;    -   MAX_(GS) is the Maximum Gray Scale (actual value of the        background or input energy)    -   ρ_(glass)=2.469 g/cm³    -   Z_(eff) _(—) _(glass)=12.12    -   a_(HI), b_(HI), a_(Lo) and b_(Lo) are constants that are        dependent on the particular X-ray imaging system used for the        scanning. The values of those constants are obtained during the        calibration phase of the machine and they are stored in the        memory 302 of the processing module 200.

The glass density (ρ_(glass)) and effective atomic number (Z_(eff) _(—)_(glass)) are stored in the memory 302 of the processing module 200.Alternatively, the glass density and effective atomic number could bestored in the knowledge bank 400, as a parameter of container. In thisfashion, it could be possible to provide for each glass containerspecific density and effective atomic numbers that match well thespecific container material. This could be useful if it is expected tofind in use different containers made of different glass compositionssuch that the density and the effective atomic numbers are not all thesame across the glass containers population.

Therefore, the step 2802 outputs the attenuation in the X-ray images atthe HI and at the Lo energy levels that the glass container produces.The output is supplied to step 2804 that uses this information tocompensate the HI and the Lo images accordingly. Step 2804 will bedescribed in greater detail later.

Assuming now that instead of estimated wall thickness information, realwall thickness information is available, then the step 2802 is performedonly if the material from which the container is made is glass.Specifically, at decision step 2808 the material from which thecontainer is made is verified. The material from which the container ismade is stored in the knowledge bank 400. If the material is glass thenstep 2802 described above is performed. On the other hand, if thematerial is plastic then the processing goes directly to the output2810. In other words, if the container is made of plastic, no imagecompensation is performed. The reason for bypassing the imagecompensation is that a plastic introduces a negligible degree of X-rayattenuation, therefore the HI and the Lo images do not need to becompensated.

Step 2804 receives the X-ray attenuation introduced by the glasscontainer for the HI and the Lo energy levels. Also, step 2804 receivesthe HI and the Lo images compensated for the belt and the tray and thecontainer contour information. Step 2804 performs image processing toremove the attenuation introduced by the container in the area definedby the container contour information. The pixels in the area defined bythe container contour information are modified such that their values nolonger reflect the contribution of the attenuation introduced by theglass material. Step 2804 therefore outputs at step 2808 HI and Loimages that have been compensated for the influence on the X-rays of thebelt, the tray and the container wall. Therefore, the HI and the Loimages now provide attenuation information of the liquid and allowcomputing parameters of the liquid.

For clarity, it should be mentioned that the compensation for thecontainer wall has essentially the effect to “remove” the container wallin the x-ray image within the contour of the container. In other wordsthe portion of the wall that is generally parallel to the x-ray imageplane is being erased. The wall portions of the container that aregenerally perpendicular to the x-ray image plane and which would defineits contour still remain in the image.

Since the HI and Lo X-ray images are two dimensional, the path lengthcalculation, in one non-limiting example of implementation, is anindirect mathematical operation based on a combination of trigonometryoperations and shape recognition algorithms. Knowing the exact physicalcharacteristics of the X-ray imaging system, it is possible to calculatethe height of the liquid container, and therefore the path lengthsfollowed by the X-ray beams, by using the position of the container onthe conveyor belt 802 with respect to the fixed reference points of theX-ray scanner itself. As these reference points remain identical fromone scan to the next, the path length calculation is not affected by therandom position of the containers in the plastic tray. Should there bebubbles in the liquid under test, their presence can be filtered out byeither appropriate filtering algorithms or by considering the bubblephysical characteristics in order to remove their contribution from theliquid.

FIG. 29 illustrates the path length determination process. FIG. 29 is across-section of the X-ray imaging system 3000 showing the belt 802 onwhich the container 3002 is placed. For clarity, the belt 802 moves thecontainer 3002 through the x-ray imaging system 3000 in a direction thatis perpendicular to the sheet. This X-ray imaging system 3000 has aradiation source 3004 that is located below the belt 802 and also anL-shaped set of detectors that has a vertical array 3006 and ahorizontal array 3008. The array 3006 is shown arbitrarily as having 12detectors, (3006 ₁ . . . 3006 ₁₂) and the array 3008 has 12 detectors(3008 ₁ . . . 3008 ₁₂) as well. Note that in practice, X-ray imagingsystems have a much higher numbers of detectors in order to provide asuitable image resolution.

The position of the source 3004 is well known and fixed. In addition,the geometry of the detector arrays 3006 and 3008 is such that it ispossible to map portions of the x-ray image (Lo and Hi) to individualdetectors of the arrays 3006 and 3008. In other words, it is possible totell for a certain portion of the image, which ones of the detectorsproduced that portion of the image. FIG. 32 provides more details inthis regard. FIG. 32 shows a simulated x-ray image of a body of liquid3002, shaped in the form of a container. The image is obtained as aresult of a movement of the container 3002 by the belt 802 with relationto the detector arrays 3006 and 3008. Therefore, individual detectors ofthe arrays 3006, 3008 produce individual bands in the image. The imagebands are shown in FIG. 32 and for clarity numbered with thecorresponding detector reference numerals.

Referring back to FIG. 29 assume for the sake of this example that theX-ray source 3004 is turned on and generates X-ray beams that aredirected through the container 3002. While there are many beams passingthrough the container 3002, consider only two of them, namely the beam3010 and the beam 3012 that intersect the top and bottom edges of thecontainer 3002. The beam 3010 will reach the detector 3008 ₂ while thebeam 3012 will reach the detector 3008 ₇. By analyzing the image it ispossible to determine which detectors of the arrays 3006, 3008 receivedthe beams 3010 and 3012. Specifically, the features of the container3002 through which the beams 3010 and 3012 pass are first located in theimage and their respective positions in the image noted. In particularthe processing module processed the x-ray image information to locatethe top and the bottom edges of the container 3002 and once thosefeatures have been identified, their position in the image is recorded.Since the image positions are mapped to corresponding detectors of thearrays 3006 and 3008, it is possible to derive which ones of thedetectors in the arrays 3006, 3008 received the beams 3010 and 3012. Onthe basis of the position of those features in the image, the detectorsare identified. Once the Identity of the detectors has bee found, bothlengths L1 and L2 can be trigonometrically calculated using angles alphaand beta. Finally, the path length H can be simply derived by theformula H=(L₁−L₂)tan α. In this example, H would be the height of thebody of liquid held in the container.

The above process works well for containers that are generallyrectangular in shape. For containers that are rounded, such ascylindrical shapes for instance, the following cylinder parametricequation can be used:

(z,θ)=u(z,θ)[cos θî+sin θĵ)]+z·{circumflex over (k)}

Where u(z,θ) will be adjusted according to every individual shape ofcontainer.

This equation is a known ray casting formula that is used to calculateobject interceptions in 3d space.

Once the path length through the liquid has been computed at step 726,the process continues at step 738 where the density and the effectiveatomic number of the liquid are computed. The process will be describedin greater detail in conjunction with the flowchart on FIG. 26. Theprocess starts at step 2700. The information that is used to perform thevarious computations includes:

-   -   1. The HI and the Lo images as output from the processing at        step 734 (the contribution of the belt, the tray and the        container wall have been removed).    -   2. HI, Lo (bgnd) which are the images compensated for the        presence of the belt.    -   3. Coordinates in the HI and the Lo images that are within the        boundary of the liquid body in the container, where the density        and the effective atomic number will be assessed. Typically, to        obtain a better accuracy the density and the effective atomic        number will be assessed at more than one location.    -   4. The path length (height of the liquid body) at the        coordinates specified at 3. Both the coordinates and the path        length values are obtained from the processing at step 726.

Step 2702 receives the HI and the Lo image information as well as thecoordinates where the density and effective atomic numbers will beassessed. The processing at step 2702 will essentially extract from theHI and the Lo images the grey level values at each of the coordinates.If each coordinate is larger than a single pixel, say it encompassesseveral pixels in the HI and the Lo images, then the grey levelextraction could include averaging the grey level values encompassedwithin each coordinate area. Therefore, the processing at step 2702outputs two sets of grey level values, the first set extracted from theHI image and the second extracted from the Lo image.

The two sets of grey level values are handled by the process at step2704. That step computes the X-ray attenuation coefficients for each ofthe coordinates. So, in addition to the grey level values sets, theprocess at step 2704 also receives the path length values from step2700, where each path length value is associated to a given coordinate.As mentioned above, a given path length value is essentially thethickness of the body of fluid through which the X-rays pass. Note thatthe path length is not necessarily the same for all the coordinates.

The processing at step 2704 applies the following algorithm forcomputing the attenuation coefficient for the various coordinates at theHI energy level:

$\mspace{20mu} {\text{?} = {\frac{1}{\text{?}} \times {{Ln}\left( \frac{\text{?}}{\text{?}} \right)}}}$?indicates text missing or illegible when filed

Where:

-   -   1. μ_(HI) _(1 . . . n) is the attenuation coefficient at the HI        energy level for the coordinates 1 . . . n;    -   2. XPL_(1 . . . n) is the path length at coordinates 1 . . . n        for the HI energy level;    -   3. E_(HI(bgnd)) at coordinates 1 . . . n for the HI energy        level;    -   4. E_(HI(final)) _(1 . . . n) are the grey level values at        coordinates 1 . . . n for the HI energy level.

A similar equation is used to compute the attenuation coefficients atthe various coordinates at the Lo energy level.

$\mspace{20mu} {\text{?} = {\frac{1}{\text{?}} \times {{Ln}\left( \frac{\text{?}}{\text{?}} \right)}}}$?indicates text missing or illegible when filed

Where:

-   -   1. μ_(Lo) _(1 . . . n) is the attenuation coefficient at the HI        energy level for the coordinates 1 . . . n;    -   2. XPL_(1 . . . n) is the path length at coordinates 1 . . . n        for the HI energy level;    -   3. E_(Lo(bgnd)) at coordinates 1 . . . n for the HI energy        level;    -   4. E_(Lo(final)) _(1 . . . n) are the grey level values at        coordinates 1 . . . n for the HI energy level.

The processing continues at steps 2706 and 2708 that compute the densityof the liquid and the effective atomic number of the liquid at therespective coordinates. The density computation at step 2706 receives asInput the X-ray attenuation coefficients, and machine calibrationconstants. Specifically, the density computation is effected by usingthe following algorithm:

$\mspace{20mu} {\rho_{1\mspace{11mu} \ldots \mspace{11mu} n} = \frac{\left( {a_{Hi} \times \text{?}} \right) - \left( {a_{Lo} \times \text{?}} \right)}{\left( {a_{Hi} \times b_{Lo}} \right) - \left( {a_{Lo} \times b_{Hi}} \right)}}$?indicates text missing or illegible when filed

Where:

-   -   1. ρ_(1 . . . n) is the density of the liquid at the coordinates        1 . . . n. Note that the density computation uses grey level        information from both the HI and the Lo X-ray images;    -   2. a_(Hi), a_(Lo),b_(Hi), b_(Lo) are X-ray imaging system        constants. These constants are stored in the memory 302 of the        processing module 200;    -   3. μ_(Lo) _(1 . . . n) is the attenuation coefficient at the HI        energy level for the coordinates 1 . . . n;    -   4. μ_(Hi) _(1 . . . n) is the attenuation coefficient at the HI        energy level for the coordinates 1 . . . n.

Step 2708 computes the effective atomic number at the coordinates 1 . .. n. This computation also makes use of the attenuation coefficientscomputed earlier for the HI and Lo energy levels and also uses the X-rayimaging system constants. Specifically, the following algorithm can beused to perform the computation:

$\mspace{20mu} {Z_{{eff}_{1\mspace{11mu} \ldots \mspace{11mu} n}} = {2.94\sqrt{\frac{\left. {{- b_{Hi}} \times \text{?}} \right) + \left( {\text{?} \times \text{?}} \right)}{\left( {a_{Hi} \times \mu_{{Lo}_{1\mspace{11mu} \ldots \mspace{11mu} n}}} \right) - \left( {a_{Lo} \times \text{?}} \right)}}}}$?indicates text missing or illegible when filed

Where:

-   -   1. Z_(eff) _(1 . . . n) is the effective atomic number of the        liquid measured at the coordinates 1 . . . n;    -   2. a_(Hi), a_(Lo), b_(Hi), b_(Lo) are X-ray imaging system        constants. These constants are stored in the memory 302 of the        processing module 200;    -   3. μ_(Lo) _(1 . . . n) is the attenuation coefficient at the HI        energy level for the coordinates 1 . . . n;    -   4. μ_(Hi) _(1 . . . n) is the attenuation coefficient at the HI        energy level for the coordinates 1 . . . n.

Finally, step 2710 outputs the density and the effective atomic numberfor each or the 1 . . . n coordinates.

Referring back to the flowchart of FIG. 7, the computation of thedensity and the effective atomic number at step 738 leads to step 741where a determination is made as to whether or not the product that wasscanned by the X-ray imaging system is a security threat. Thisdetermination will be described in greater detail in connection with theflowchart on FIG. 28. The process starts at step 2900. The processing atstep 2900 receives the following information:

-   -   1. Z_(eff) _(1 . . . n) is the effective atomic number of the        liquid measured at the coordinates 1 . . . n, as computed at        step 738.    -   2. ρ_(1 . . . n) is the density of the liquid at the coordinates        1 . . . n, also as computed at step 738.    -   3. (Δρ,Δ_(Zeff))_(sys) which is the system error or standard        error generated by the system itself.

Step 2902 computes an average density value for the liquid and also thestandard deviation. Specifically, the average density is determined by:

$\rho_{average} = {\frac{1}{n}{\sum\limits_{i = 1}^{n}\; \rho_{i}}}$

Where:

-   -   1. ρ_(average) is the average density of the liquid.

Step 2902 also computes the standard deviation Δρ of ρ_(1 . . . n) withrelation to ρ_(average). The standard deviation is expressed by Δρ=σ(ρ₁,ρ₂, ρ₃, . . . ρ_(n)).

Similarly, step 2904 computes the average effective atomic number alongwith the standard deviation. Specifically, the average effective atomicnumber is determined by:

$\mspace{20mu} {Z_{{eff}\text{-}{average}} = {\frac{1}{n}{\sum\limits_{i = 1}^{n}\; \text{?}}}}$?indicates text missing or illegible when filed

Where:

-   -   1. Z_(eff-average) is the average effective atomic number of the        liquid.

Step 2904 also computes the standard deviation ΔZ_(eff) of Z_(eff)_(1 . . . n) with relation to Z_(eff-average). The standard deviation isexpressed by ΔZ_(eff)=σ(Z_(eff) ₁ , Z_(eff) ₂ , Z_(eff) ₃ , . . .Z_(eff) _(n) ).

Steps 2902 and 2904 output to step 2906, which is the next step in theprocessing thread, ρ_(average), Δρ, Z_(eff-average), ΔZ_(eff), Δρ_(sys)and ΔZ_(eff-sys).

Step 2906 generates density and effective atomic number lookup values toquery the knowledge bank 400. More specifically, the processing at step2906 computes an effective atomic number lookup window to selectpotential matching candidates in the knowledge bank 400. This lookupwindow is mathematically defined as:

[Z _(eff-LU) ]Z _(eff-average)±Σ(ΔZ _(eff) +ΔZ _(eff-sys))

The lookup window is defined by a low effective atomic number valueZ_(eff-LU-Low) and by a high effective atomic number valueZ_(eff-LU-Hi).

The density lookup window is mathematically defined as:[ρ_(LU)]=ρ_(average)±Σ(Δρ+Δρ_(sys)). The lookup window is defined by loweffective density value ρ_(LU-low) and by a high effective atomic numbervalue ρ_(LU-high).

The knowledge bank 400 is queried on the basis of the density andeffective atomic number lookup windows. The selection process is suchthat a product in the knowledge bank 400 for which an effective atomicnumber and a density value fall in the respective lookup windows areretained as potential candidates. The list of candidates is thenprocessed at step 2910 that determines if the liquid poses a securitythreat. More specifically, the processing at step 2910 tries todetermine to what degree anyone of the candidates matches thecharacteristics of the product scanned by the X-ray imaging system.

A “candidate” is essentially an entry in the knowledge bank 400. Most ofthose entries are likely to be associated to commercially availableproducts such as product for human consumption (water, juice, softdrinks, etc.) and personal hygiene product (shampoo, toothpaste,deodorant, skin care cream, washing gel, etc.), among others thatpassengers are likely to have in hand carried baggage. As discussedearlier, each candidate that is selected at step 2908 is defined bycertain characterizing information, such as density, effective atomicnumber and container characterization among others. This characterizinginformation is then compared with the product characterization effectedas a result of the X-ray scan to determine if a match can be found. If amatch exists, this means that in all likelihood the liquid in thecontainer that was scanned by the X-ray imaging system is “genuine” inother words matches the labelling on the container. So, if the productthat is being scanned is a liquid filled container, where the containeris labelled as a bottle of water, a match would indicate that in allprobability the liquid is water and has not been substituted bysomething else.

The process for determining if the product characterization matches anyone of the candidates involves comparing the product characterizationwith the information that characterizes each candidate. In a specificand non-limiting example of implementation, a first comparison is madebetween the density (as computed from the X-ray images) of the scannedproduct and the density information for each one of the candidates. Thecandidate that matches best the density of the scanned product isretained. Next, the effective atomic number (as computed from the X-rayimages) of the product is compared to the effective atomic number of thecandidate that was retained. If a match is found then the final step ofthe assessment includes comparing the container features identified fromthe X-ray images with the container features stored for that candidatein the knowledge bank 400. If a match is found then the system concludesthat the product that was scanned by the X-ray imaging system isauthentic and corresponds to the candidate.

The decision as to whether or not the scanned product is a securitythreat depends on the nature of the candidate. If the candidate isIdentified in the knowledge bank 400 as being “safe” then scannedproduct is deemed safe too. On the other hand, if the scanned productmatches a candidate that is deemed “illegal” such as for example aflammable liquid or another dangerous chemical, then the scanned productwould be deemed “unsafe”.

In instances where no match can be found between the scanned product anda candidate, which occurs when the effective atomic number of the bestcandidate (the candidate retained subsequent to the density comparison)does not match the effective atomic number of the scanned product, orwhen the container characterization of the best candidate does not matchthe container characterization of the scanned product, the systemassumes that the scanned product is suspect and triggers an alert. Thissituation would occur if a passenger would be attempting to pass at thesecurity check point a container labelled as a common “safe” productsuch as a soft drink bottle, in which the soft drink has been replacedby another liquid, which has a different density and/or effective atomicnumber than the soft drink.

There are many other threat assessment strategies that can be usedwithout departing from the spirit of the invention. For instance, theknowledge bank 400 can be augmented to include scattering/diffractionsignatures of the Various entries stored therein. In this fashion, thesystem would be provided with an additional parameter that can be usedto decide if a match exists between the scanned product and anyone ofthe knowledge bank 400 entries.

Note that in instances where the container of the scanned product can bealone used to identify a specific entry in the knowledge bank 400, thenthe threat assessment process at step 2910 would be greatly simplifiedsince a candidate exists to which the scanned product is being compared.

After the threat assessment has been completed, the system issues viathe user interface the decision, which in one example could be a simple“pass” indicating that the product is safe or “fail” indicating that nomatch was found which would prompt a rejection of the product (thepassenger would not be allowed to proceed with it) or a manualsearch/inspection in an attempt to identify with greater precision thenature of the product.

The flow chart in FIG. 19 a Illustrates another example of inimplementation of the Invention where the characterization of theproduct is made by reference to the Universal Product Code (UPC) barcode that appears on the product. Nearly all the products that are soldtoday in the market use a bar code system that facilitate checkoutprocedures and also help tracking inventories. UPC barcodes originatewith the Uniform Product Council that manages the allocation of thebarcodes to different manufacturers. A typical bar code that is appliedto the product package has generally two components; one is the machinereadable part and the other the human readable part. The machinereadable part appears as a series of bars while the human readable partis a series of digits appearing below the machine readable bars. Atypical UPC bar code has a part that identifies the manufacturer andanother part that identifies the actual product within thatmanufacturer's product line. Since UPC barcodes are used primarily forpayment and inventory control purposes they are unique for each product.Accordingly, the UPC barcode constitutes a unique identifier for almostevery product that is found in market today.

The process at the flowchart of FIG. 19 a starts at step 1900 where thebar code of the product (container+liquid) whose security status is tobe established is read. This operation is performed by using a standardbar code reader of a type known in the art. The information obtained asa result of the reading operation is then used to search a knowledgebank 1902 and usually will be sufficient to uniquely Identify theproduct among the plurality of products stored in the knowledge bank1902.

The structure of the knowledge bank is shown in FIG. 19 b. Theinformation in the knowledge bank 1908 can be organized as a table. Eachentry of the table is associated with a certain liquid product.Typically, the products in the table are those that are most likely tobe carried by passengers a security checkpoint. Examples include bottledwater, soft drinks, and juice and cosmetic/healthcare products, amongothers. Each entry of the knowledge bank is identified by the UPC barcode applied on the product by its manufacturer. Since bar codes areunique, that entry conveniently constitutes a key on the basis of whichthe knowledge bank 1908 can be searched. In the specific example ofimplementation shown at FIG. 19 b, the knowledge bank 1908 has sevendata fields for each entry. The data fields are as follows:

-   1) The UPC bar code that is expressed in any suitable format.-   2) The density of the liquid. The density may be the real density    (as measured by standard techniques) or the density as assessed as a    result of an X-ray scan, or both. In this example, only one density    value is shown assuming that the real density and the one obtained    as a result of an X-ray scan are the same.-   3) The effective atomic number of the liquid as measured by X-rays.-   4) Container features, such as visual characteristics that    distinguish the container. Examples include the dimensions of the    container (height and transverse dimensions), type of container    (screw cap, can or other), general container shape (cylindrical,    rectangular cross-section, etc), and unique visual features such as    ridges or projections on the walls, among many others. One    possibility is to store in this data field a 3d image of the product    that would show the product from different sides. With the    appropriate image viewer, the operator can, therefore be provided    with a complete image of the product that was found to match the    barcode search operation. The container features also include    Information on the wall thickness and the material from which the    wall is made such as to allow compensating the X-ray image data for    the attenuation by the container walls.-   5) The diffraction/back scatter signature.-   6) The product identification. This could be the name/brand of the    product, as it appears on the label of the product. The Information    can be stored as an image of the label to allow the operator to see    on a computer screen how the label looks.-   7) The threat status. This indicates if the product is safe or not    safe. For instance, the first three products in the table are common    household items that crate no danger. Accordingly, if the screening    operation confirms that products carried by passengers at the    security check point correspond to anyone of those entries, then the    products are deemed safe. On the other hand if a product is    Identified as matching the last entry, namely a strong acid, an    alarm should be triggered on the basis of the fact that the product    is not allowed beyond the checkpoint.

It should be recognized that the structure of the knowledge bank 1908can include more information about liquid products or less information,without departing from the spirit of the invention.

Referring back to FIG. 19 a, step 1904 determines the response of theliquid in the container to penetrating radiation, X-rays in particular.This can be done in the same way as described previously under the firstexample of implementation. In short, step 1904 will derive parameters ofthe liquid from the X-ray scan, such as density, effective atomicnumber, and diffraction/back scatter signature, among others. This canbe done by referring or using Information stored in the knowledge bank1908, such as for example the thickness of the container wall and thematerial from which the container wall is made such as to perform X-rayimage compensation for the attenuation of the X-rays by the containerwall.

Next, the comparison step 1906 determines the threat status of theliquid product. This is done by comparing parameters of the liquidproduct as extracted from the knowledge bank to those measured by theX-ray scan. Assume for the sake of this example, that at step 1900 thebar code on the container was correctly read and the search step 1902identified an entry in the knowledge bank on the basis of the bar code.The comparison step 1906 will then read the data associated with thisentry, such as the density and effective atomic number of the liquid,the container features, diffraction/back scatter signature, productinformation and threat status. Next, step 1906 will compare theparameters such as the density, effective atomic number and/ordiffraction/backscatter signature to the parameters that were assessedby the X-ray inspection.

The results of the comparison are passed to step 1910 that performs thethreat assessment. If there is a match between the parameters read fromthe knowledge bank and those measured by the X-ray Inspection machine,then the process assumes that the container that is being inspectedcontains a liquid that is consistent with the label on the container; inother words the liquid in the original container has not beensubstituted by something else. Accordingly, if no substitution has beenmade and the container contains the original product, then the threatassessment step displays or otherwise communicates to the operator thethreat status from the matching entry in the knowledge bank. Forinstance if the matching entry is associated with a product that has“safe” threat status, then the step 1910 will conclude that the productcan be carried beyond the check point. Otherwise, when the matchingentry is associated with an “unsafe” product the step 1910 will notifythe security operator accordingly.

On the other hand, if no match is found between the parameters read fromthe knowledge bank and those measured by the X-ray inspection machine,the logic concludes that the liquid in the container is different fromwhat the label says. This is a strong indication that the originalliquid has been substituted by something else, in which case the productis deemed “unsafe”.

FIG. 20 is a block diagram of the equipment used to implement the methoddescribed in FIG. 19 a. The installation is very similar to the set-updescribed in connection with FIG. 1 and for that reason wheneverpossible similar reference numbers will be used. The main distinctionresides in the addition of a bar code reader 2000 that generates a barcode signal on output 2002 conveying the bar codes scanned by the reader2000. The output 2002 connects to the processing module 200.

In this example of implementation the bar code reader 2000 is separatefrom the X-ray apparatus 100. Specifically, the bar code reader 2000 maybe a hand-held reader of the type commonly used at checkout paymentstations, in stores. Alternatively, the bar code reader 2000 may be astationary device that has a reading window. The container is presentedin front of the reading window to allow the bar code to be read.

In the case of a hand held bar code reader 2000, the operator 130 wouldscan the liquid product whose threat level is to be assessed such as toread the bar code. Once the bar code is acquired, the knowledge bank1908 is searched by the processing module 200 to locate the entryassociated with that code. If the entry in the knowledge bank 1908 isidentified, information about the entry can be displayed on the operatorconsole 350. For instance one or more container features can be visuallyshown on the console 350, such as a three-dimensional image of thecontainer, allowing the operator to visually confirm that the entry inthe knowledge bank 1908 indeed matches the container that was scanned.

Next, the operator 130 processes the container as discussed earlier. Inparticular, the liquid product is placed in the tray and the tray put onthe conveyor belt of the X-ray apparatus 100. The X-ray scan isperformed and the results are passed to the processing module 200. Theprocessing module will process the X-ray image data to extract theresponse of the liquid in the container to the X-rays. The response iscompared to the parameters stored in the previously identified knowledgebank 1908 entry.

The results of the threat assessment performed by the processing module200 can then be displayed on the operator console 350.

In the instance where the bar code reader is a fixed device, it can beintegrated in the X-ray apparatus such that the bar code on eachcontainer is read as the liquid product is put on the conveyor belt.This may require positioning the containers in the tray in such a way asto leave the bar codes exposed.

The reader will appreciate that many options exist to position the barcode reader in a way to suit a wide variety of possible applications.

In a possible variant, the bar code reader can be replaced with a RadioFrequency Identification (RFID) tags reader, suitable for liquidproducts that use such RFID tags for identification purposes. Morespecifically, RFID tags have an antennae and a small electronic circuitholding the information to supply when the RFID tag is interrogated.RFID tags can be read over relatively short distances (10 feet or less)and the reading does not have to be in the line of sight of the reader.In this type of application the liquid product to be scanned may bepassed close to an RFID tag reader that will gather the identifyinginformation. For instance, the RFID tag reader may be integrated to theX-ray apparatus 106 adjacent the conveyor of the X-ray apparatus. As theliquid product is put in the tray on the conveyor the liquid productwill pass close enough the RFID tag reader for the reading operation totake place.

It is desirable to provide a knowledge bank 1908 that is as extensive aspossible. In this fashion, most of the liquid products that a passengeris likely to carry through the security checkpoint can be referenced toan entry in the knowledge bank, allowing to precisely determine if theliquid product is a threat or not Building the knowledge bank 1908 wouldinvolve gathering the necessary information for a wide variety of liquidproducts and then entering that information in the database that wouldconstitute the knowledge bank 1908.

Gathering the initial information may be done by purchasing the liquidproducts that should be referenced in the knowledge bank 1908 andperforming an analysis to obtain the necessary data. For Instance, foreach product the bar code on the container is read with a bar codereader and the information stored. Next the container is analysed togenerate the various features of interest that are to be stored in theknowledge bank 1908, such as its visual features, container wallthickness and material from which the container wall is made. Finally,the response of the liquid product to X-rays is determined and theresulting parameters such as density, effective atomic number and/ordiffraction/scattering signature obtained.

One simplified way of obtaining the response of the liquid to X-rays isto process the liquid product in the X-ray apparatus 100 as per theprocess described in the flowchart of FIG. 7. Once the container wallsthickness and container wall material is known, the computation of theliquid density, effective atomic number and/or diffraction scatteringsignature can be made on the basis of the information contained in theX-ray image.

The information generated as a result of this initial data gathering isloaded in the knowledge bank 1908, which as discussed previously, is inthe form of a database. The database can be structured in any suitablefashion, on any suitable computer readable medium, without departingfrom the spirit of the invention.

In use, the system shown in FIG. 1 a or 20 would be operated at securitycheck points such as at airports. The entity that operates the unitswould normally be a government agency or a private contractor mandatedby the government to enforce security at the checkpoints. In order toperform adequately, the system should be updated regularly to keepknowledge bank 1908 current. Specifically, the knowledge bank 1908should be updated periodically to reference new liquid products that arebeing released on the market and that are susceptible to be carried bypassengers through the security checkpoint.

The knowledge bank updating Information is illustrated by the flowcharton FIG. 21. Initially, a list is obtained on the new products that havebeen recently commercialized and that should be loaded in the knowledgebank 1908. This can be done in various ways. For instance, manufacturersof products that are most likely to be carried through the check pointmay be queried to determine what are the new products that have beenreleased in the market since the last knowledge bank 1908 update cycle.Once the list of those products is set, then samples are obtained. Atstep 2100 the samples are processed as discussed previously to extractthe relevant data. The relevant data is then loaded in the knowledgebank 1908, at step 2102

The knowledge bank 1908, either in its entirety or only the updated partis transmitted to the various locations that use it to perform securityscreening. The transmission can be done electronically, such as over theInternet or manually by recording the update on a portable machinereadable medium, which is then loaded in a reader on the computer thatmanages the knowledge bank 1908. This operation is shown at step 2104.The number of locations that need to be updated will depend upon themanner in which the individual security checkpoints work. If eachsecurity checkpoint is a stand alone unit and has its own knowledge bank1908, then each security checkpoint has to be updated individually. Onthe other hand, if the security checkpoints are networked, a moreautomated updating procedure is possible. For instance, if the networkis such that a common knowledge bank 1908 is provided which services aplurality of security checkpoints, then a single update is sufficient.On the other hand, if the networked arrangement uses a plurality ofknowledge banks local to the respective security checkpoints, then thedata to perform the update can be electronically sent in the field tothe various security checkpoints to make local updates.

The knowledge bank update would normally be in the form of asubscription or available on demand. In this fashion the entity thatperforms the knowledge bank 1908 update will charge the end user(government entity or private contractor) for the updates. The financialarrangements can vary and many may be in the form of a fixed feearrangement valid for a predetermined time period, say one year. Duringthe subscription period the end user receives automatically updates, assoon as they become available. When the update is done on demand, thenan update is sent only when requested and a payment is made by the enduser after reception of the service.

Although various embodiments have been illustrated, this was for thepurpose of describing, but not limiting, the invention. Variousmodifications will become apparent to those skilled in the art and arewithin the scope of this invention, which is defined more particularlyby the attached claims.

1-94. (canceled) 95) A method for performing liquid product threatstatus determination, said method comprising: a. scanning two or moreliquid products concurrently with an X-ray scanner to generate X-rayimage data conveying an image of the two or more liquid products, eachliquid product being comprised of a container holding a body of liquid;b. processing the X-ray image data with software executed by a CPU todetermine if one of the liquid products in the image is a securitythreat; c. displaying on a display means an image of the liquid productsderived from the X-ray image data, wherein displaying the image of theliquid products includes visually enhancing under control of thesoftware the one liquid product such that it is visually distinguishablefrom another liquid product in the image. 96) A method as defined inclaim 95, wherein the X-ray scanner is a single view X-ray scanner. 97)A method as defined in claim 95, wherein the X-ray image data conveysX-ray attenuation information. 98) A method as defined in claim 97,wherein the software executed by the CPU is responsive to an input by ahuman operator designating on the display means the one liquid productto process X-ray attenuation information in an area of the imageassociated with the one liquid product designated by the human operatorto determine the threat status of the one liquid product. 99) A methodas defined in claim 98, wherein said method comprising implementing onthe display means a Graphical User Interface (GUI), the graphical userinterface including a display area for displaying the image of theliquid products. 100) A method as defined in claim 99, wherein theGraphical User Interface (GUI) includes at least one tool for allowingthe human operator to provide the input designating the one liquidproduct. 101) A method as defined in claim 100, wherein the toolincludes a pointing device. 102) A method as defined in claim 100,wherein the tool includes a touch sensitive surface on the displaymeans. 103) A method as defined in claim 100, wherein the input conveysa designation of an edge of the one liquid product. 104) A method asdefined in claim 100, wherein the input conveys a zone curtailing aportion of the image where the one liquid product lies. 105) A method asdefined in claim 103, wherein the software executed by the CPU isresponsive to the input to process the X-ray image data to identify thearea of the image associated with the one liquid product at least inpart based on the designation of the edge. 106) A method as defined inclaim 104, wherein the software executed by the CPU is responsive to theinput to process the X-ray image data to identify the area of the imageassociated with the one liquid product at least in part based on thezone conveyed by the input. 107) A method as defined in claim 95,wherein visually enhancing the one liquid product includes highlightingan edge of the one liquid product in the image. 108) A method as definedin claim 95, wherein visually enhancing the one liquid product includeshighlighting the one liquid product in its entirety in the image. 109) Amethod as defined in claim 95, wherein visually enhancing the one liquidproduct includes de-emphasizing areas in the image except an area of theimage where the one liquid product lies. 110) An apparatus forperforming liquid product threat status determination, said apparatuscomprising: a. an input for receiving X-ray image data conveying animage of two or more liquid products concurrently scanned with an X-rayscanner, each liquid product being comprised of a container holding abody of liquid; b. a processor in communication with said input, saidprocessor being programmed with software for: i. processing the X-rayimage data to determine if one of the liquid products in the image is asecurity threat; ii. processing the X-ray image data to generate imagesignals derived from the X-ray image for driving a display means, theimage signals displaying on the display means an image of the liquidproducts derived from the X-ray image data, wherein displaying the imageof the liquid products includes visually enhancing the one liquidproduct such that it is visually distinguishable from another liquidproduct in the image; c. an output in communication with said processorfor releasing the image signal. 111) An apparatus as defined in claim110, wherein the X-ray scanner is a single view X-ray scanner. 112) Anapparatus as defined in claim 110, wherein the X-ray image data conveysX-ray attenuation information. 113) An apparatus as defined in claim112, wherein the processor is programmed to be responsive to an input bya human operator designating on the display means the one liquid productto process X-ray attenuation information in an area of the imageassociated with the one liquid product designated by the human operatorto determine the threat status of the one liquid product. 114) Anapparatus as defined in claim 113, wherein the processor is programmedto implement on the display means a Graphical User Interface (GUI), thegraphical user interface including a display area for displaying theimage of the liquid products. 115) An apparatus as defined in claim 114,wherein the Graphical User Interface (GUI) includes at least one toolfor allowing the human operator to provide the input designating the oneliquid product. 116) An apparatus as defined in claim 115, wherein thetool includes a pointing device. 117) An apparatus as defined in claim115, wherein the tool includes a touch sensitive surface on the displaymeans. 118) An apparatus as defined in claim 115, wherein the inputconveys a designation of an edge of the one liquid product. 119) Anapparatus as defined in claim 115, wherein the input conveys a zonecurtailing a portion of the image where the one liquid product lies.120) An apparatus as defined in claim 118, wherein the processor isprogrammed to be responsive to the input to process the X-ray image datato identify the area of the image associated with the one liquid productat least in part based on the designation of the edge. 121) An apparatusas defined in claim 119, wherein the processor is programmed to beresponsive to the input to process the X-ray image data to identify thearea of the image associated with the one liquid product at least inpart based on the zone conveyed by the input. 122) An apparatus asdefined in claim 110, wherein visually enhancing the one liquid productincludes highlighting an edge of the one liquid product in the image.123) An apparatus as defined in claim 110, wherein visually enhancingthe one liquid product includes highlighting the one liquid product inits entirety in the image. 124) An apparatus as defined in claim 110,wherein visually enhancing the one liquid product includesde-emphasizing areas in the image except an area of the image where theone liquid product lies.